Methods of this type for object tracking, so-called tracking methods, are generally known. Applications are also already known in the automotive sector in which tracking methods are used to track and predict the movement of a pedestrian or also of a cyclist or of another vehicle, so that an impending collision can be predicted at an early stage. The vehicle can be braked via a driver assistance system in the event of an impending collision, in particular with a pedestrian, or suitable safety devices can be activated. Alternatively or additionally, an alarm signal can be emitted to warn the driver.
A difficulty of such applications in this connection is that not only the object to be tracked, for example a pedestrian, is moving, but also the camera fixed to the vehicle. These two movements overlap and the resulting movement between two images taken sequentially by the camera device is difficult to model. It has previously not been possible to provide a satisfactory method for object tracking with the assistance of a moving camera. On the one hand, the quality of the predictions which can be achieved with conventional processes is often not satisfactory; on the other hand, a comparatively large computing power is needed to evaluate the images taken by the camera in real time.